Please use this identifier to cite or link to this item: http://dx.doi.org/10.18419/opus-10627
Authors: Hose, Dominik
Hanss, Michael
Title: On data-based estimation of possibility distributions
Issue Date: 2019
metadata.ubs.publikation.typ: Preprint
metadata.ubs.publikation.seiten: 16
URI: http://elib.uni-stuttgart.de/handle/11682/10644
http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-106448
http://dx.doi.org/10.18419/opus-10627
metadata.ubs.bemerkung.extern: Preprint submitted to Fuzzy Sets and Systems on October 14, 2019.
Abstract: In this paper, we show how a possibilistic description of uncertainty arises very naturally in statistical data analysis. In combination with recent results in inverse uncertainty propagation and the consistent aggregation of marginal possibility distributions, this estimation procedure enables a very general approach to possibilistic identification problems in the framework of imprecise probabilities, i.e. the non-parametric estimation of possibility distributions of uncertain variables from data with a clear interpretation.
Appears in Collections:07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik

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